GalPaK v1.8.8

Overview

GalPaK 3D is a tool to extract the intrinsic (i.e. deconvolved)
Galaxy Parameters and Kinematics from any 3-Dimensional data.
The algorithm uses a disk parametric model with 10 free parameters
(which can also be fixed independently) and a MCMC approach with
non-traditional sampling laws in order to efficiently probe the
parameter space.

More importantly, it uses the knowledge of the 3-dimensional
spread-function to return the intrinsic galaxy properties and the
intrinsic data-cube. The 3D spread-function class is flexible enough to
handle any instrument.

One can use such an algorithm to constrain simultaneously the kinematics
and morphological parameters of (non-merging, i.e. regular) galaxies
observed in non-optimal seeing conditions.
The algorithm can also be used on AO data or on high-quality, high-SNR
data to look for non-axisymmetric structures in the residuals.

2014-07-21 &ac; The website is up

Demo

The following video was made using these parameters :
from galpak import GalPaK3D, MUSEWFM
g = GalPaK3D('hyperspectral_cube.fits',
seeing=0.7,
instrument=MUSEWFM(lsf_fwhm=2.519/1e4))
g.run_mcmc(max_iterations=10000)